Question

所以，我有一个棒球运动员的数据集，我试图计算他们的体重的高度的预期值。我知道如何在一个变量中计算预期值，但我不确定如何使用另一个变量？

我在下面添加了我的数据集。使用dput命令，我想目前我已经使用各种mutate命令，但我不知道如果weightpounds = weightpounds，如何编写类似expectedheight = mean（heightunches）的东西。因为期望值需要考虑重量。

structure(
  list(Name = structure(1:3, .Label = c("Adam_Donachie", "Paul_Bako", "Ramon_Hernandez"), class = "factor"), 
       Team = structure(c(1L, 1L, 1L), .Label ="BAL", class = "factor"), 
       Position = structure(c(1L, 1L, 1L), .Label = "Catcher",class = "factor"), 
       Heightinches = c(74L, 74L, 72L), Weightpounds =c(180L, 215L, 210L), 
       Age = c(22.98999977, 34.68999863, 30.78000069)), row.names = c(NA, -3L), 
  .Names = c("Name", "Team", "Position", "Heightinches", "Weightpounds", "Age"), 
  class = "data.frame")

Answer 1

例如，您可以使用线性回归

model <- lm( Weightpounds ~ Heightinches,dat)

model

Call:
lm(formula = Weightpounds ~ Heightinches, data = dat)

Coefficients:
 (Intercept)  Heightinches  
      660.00         -6.25

意思是

Weightpounds = 660 - 6.25*Heightinches

您也可以将模型应用于数据

> model <- lm( Weightpounds ~ Heightinches,dat)
> predict(model,dat)
1     2     3 
197.5 197.5 210.0

这使用非常简单的线性模型。

您可以通过扩展公式 Weightpounds ~ Heightinches来扩展模型，以进行语法检查?formula

Y（R）的每个值的预期X值

1 个答案: